D-optimal designs for multiarm trials with dropouts.

Abstract

Multi-arm trials with follow-up on participants are commonly implemented to assess treatment effects on a population over the course of the studies. Dropout is an unavoidable issue especially when the duration of the multi-arm study is long. Its impact is often ignored at the design stage which may lead to less accurate statistical conclusions. We develop an optimal design framework for trials with repeated mea- surements which takes potential dropouts into account, and provide designs for linear mixed models where the presence of dropouts is noninformative and dependent on design variables. Our framework is illustrated through redesigning a clinical trial on Alzheimer’s disease, whereby the benefits of our designs compared with standard designs are demonstrated through simulations.